After a communication signal has traveled through a communication channel, equalization is often performed on the received signal to remove channel effects from the signal. One of the channel effects that often needs to be removed is intersymbol interference (ISI). In a wireless communication system, ISI is typically present in the form of multipath interference. That is, a transmit signal travels through the wireless channel via multiple different paths that each have a different channel delay. For example, one signal component may travel in a direct path from the transmitter to the receiver while one or more other signal components are reflected from objects in the surrounding environment toward the receiver. As can be appreciated, the signal component that travels directly to the receiver will typically be the first to arrive at the receiver and have the largest amplitude. The reflected components will typically arrive at the receiver sometime later and have smaller amplitudes. Although smaller in amplitude, the reflected signals can interfere with the direct signal making it more difficult to accurately detect the data therein. Equalization is thus used in the receiver to reduce or eliminate the negative channel effects from the received signal to improve the likelihood of accurate detection.
In most equalization techniques, an estimate of the present channel response is first determined. The channel estimate is then used to process the received signal to remove the negative channel effects. The channel estimation process is often a computationally complex and time consuming process. That is, performance of such processes will often consume a large percentage of system resources and may introduce undesirable delays in the receiver processing. As can be appreciated, it is generally desirable to reduce computational complexity and processing delays within a communication system. This is especially true within handheld and portable communication units that have limited processing capabilities and a limited supply of power (e.g., batteries). Therefore, there is a need for channel estimation techniques and structures that are computationally efficient while still providing accurate estimates.